Early Dementia Screening Research Articles

Guardians of memory: The urgency of early dementia screening in an aging society.

The global aging population has led to a significant rise in the prevalence of age-related non-communicable diseases such as dementia and other cognitive disorders. In 2019, there were 57.4 million people with dementia worldwide, and this number is projected to triple by 2050. Intervening in and managing 12 potentially modifiable dementia risk factors can prevent or delay the onset and progression of about 40% of dementia cases. Neuroimaging, biomarkers, and advanced neuropsychological testing offer promising pathways for the early detection of dementia. Emphasis should be placed on educating the public about the importance of brain health and the early signs of cognitive impairment, as well as promoting dementia prevention measures. Adopting a healthy lifestyle - including a balanced diet, regular physical exercise, active social engagement, cognitive activities, and avoiding smoking and excessive alcohol consumption - can help reduce the risk of cognitive decline and prevent cognitive disorders. Government policies on dementia prevention and health care, along with early and regular dementia screening programs, can enhance the early identification and management of individuals at risk. In addition, integrating cognitive health assessments into routine medical check-ups is essential for the early screening and management of dementia.

A portable and efficient dementia screening tool using eye tracking machine learning and virtual reality

Dementia represents a significant global health challenge, with early screening during the preclinical stage being crucial for effective management. Traditional diagnostic biomarkers for Alzheimer’s Disease, the most common form of dementia, are limited by cost and invasiveness. Mild cognitive impairment (MCI), a precursor to dementia, is currently identified through neuropsychological tests like the Montreal Cognitive Assessment (MoCA), which are not suitable for large-scale screening. Eye-tracking technology, capturing and quantifying eye movements related to cognitive behavior, has emerged as a promising tool for cognitive assessment. Subtle changes in eye movements could serve as early indicators of MCI. However, the interpretation of eye-tracking data is challenging. This study introduced a dementia screening tool, VR Eye-tracking Cognitive Assessment (VECA), using eye-tracking technology, machine learning, and virtual reality (VR) to offer a non-invasive, efficient alternative capable of large-scale deployment. VECA was conducted with 201 participants from Shenzhen Baoan Chronic Hospital, utilizing eye-tracking data captured via VR headsets to predict MoCA scores and classify cognitive impairment across different educational backgrounds. The support vector regression model employed demonstrated a high correlation (0.9) with MoCA scores, significantly outperforming baseline models. Furthermore, it established optimal cut-off scores for identifying cognitive impairment with notable sensitivity (88.5%) and specificity (83%). This study underscores VECA’s potential as a portable, efficient tool for early dementia screening, highlighting the benefits of integrating eye-tracking technology, machine learning, and VR in cognitive health assessments.

Multimodal dementia identification using lifestyle and brain lesions, a machine learning approach

Dementia diagnosis often relies on expensive and invasive neuroimaging techniques that limit access to early screening. This study proposes an innovative approach for facilitating early dementia screening by estimating diffusion tensor imaging (DTI) measures using accessible lifestyle and brain imaging factors. Conventional DTI analysis, though effective, is often hindered by high costs and limited accessibility. To address this challenge, fuzzy subtractive clustering identified 14 influential variables from the Lifestyle for Brain Health and Brain Atrophy and Lesion Index frameworks, encompassing demographics, medical conditions, lifestyle factors, and structural brain markers. A multilayer perceptron (MLP) neural network was developed using these selected variables to predict fractional anisotropy (FA), a DTI metric reflecting white matter integrity and cognitive function. The MLP model achieved promising results, with a mean squared error of 0.000 878 on the test set for FA prediction, demonstrating its potential for accurate DTI estimation without costly neuroimaging techniques. The FA values in the dataset ranged from 0 to 1, with higher values indicating greater white matter integrity. Thus, a mean squared error of 0.000 878 suggests that the model’s predictions were highly accurate compared to the observed FA values. This multifactorial approach aligns with the current understanding of dementia’s complex etiology influenced by various biological, environmental, and lifestyle factors. By integrating readily available data into a predictive model, this method enables widespread, cost-effective screening for early dementia risk assessment. The proposed accessible screening tool could facilitate timely interventions, preventive strategies, and efficient resource allocation in public health programs, ultimately improving patient outcomes and caregiver burden.

Prevalence, factors associated and knowledge of probable dementia among adults 50 years and over attending a faith-based geriatric center in Uganda

Dementia is on the rise due to increasing proportion of old people in sub-Saharan Africa (SSA). Although dementia is misattributed to normal ageing or supernatural causes in SSA, it is a brain disease with well-established etiologies. Limited knowledge and understanding of dementia means that many older people are suffering without seeking help and are undiagnosed and untreated. The aim of this study was to determine the prevalence and factors associated with probable dementia and to describe the knowledge of the disease among adults 50 years and over attending a faith-based geriatric center in Uganda. This was a cross-sectional study using quantitative methods. A total of 267 adults 50 years and over attending a faith-based geriatric center in Mukono, Uganda were interviewed between 1 April and 15 May 2022. Interviews were administered using the Early Dementia Questionnaire (EDQ) and Dementia Knowledge Assessment Scale (DKAS). Data on participants’ socio-demographics, economic income, living arrangement, history of smoking, alcohol consumption, exercise and past medical history was collected using an additional questionnaire. Adults 50 years and over were included in the study. Logistic regression analyses were done. Probable dementia was 46.2% in the sample. The most common symptoms of probable dementia in the order of their severity were memory symptoms, (β co-efficient β 0.08, p < .001), physical symptoms (β 0.08, p < .001), sleep disturbances (β 0.81, p < .001) and emotions (β 0.04, p < .027). The final degree of association as determined by adjusted PR in the multivariable model revealed that only older age (aPR = 1.88, p < .001) and occasional/non-believer (aPR = 1.61, p = .001) remained significantly related to probable dementia. The study also found that 8.0% of the participants had optimal knowledge of dementia. There is high burden of probable dementia among adults 50 years and over attending a faith-based geriatric center in Mukono, Uganda. Factors associated with probable dementia are older age and being an occasional/non-believer. Knowledge of dementia among older adults is low. There is need to promote integrated early dementia screening, care and educational program in primary care to reduce the disease burden. Spiritual support would be a rewarding investment in the lives of the ageing population.

Diagnosis of cognitive disorders in primary health care in Poland.

The aim of this study was to assess the knowledge, attitudes and the rules of proceeding concerning primary health care (PHC) doctors in the field of screening diagnostics for cognitive disorders in elderly people in Poland. The study included 175 PHC doctors. A validated anonymous questionnaire was used. The survey was conducted using the PAPI (Paper and Pencil Interviews) and CAWI (Computer Assisted Web Interviews) methods. The vast majority of the respondents (n=159; 91.4%) saw the advisability of screening for cognitive disorders in the age group >65 years of age, but only 53 subjects (30.29%) believed that these tests should be conducted by general practitioners (GPs). According to the surveyed doctors, the main obstacle in the diagnostics of cognitive functions is the lack of time - this was the opinion of 142 (81.14%) respondents. When dementia was suspected, the respondents usually ordered laboratory tests and referred patients to a neurologist (n=111; 63.4%). The Mini Mental Status Examination (MMSE) and the Clock Drawing Test (CDT) were the most popular scales assessing cognitive functions, known by 120 doctors (68.57%), and 122 respondents (69.71%), respectively. Polish GPs are aware of the necessity of screening for cognitive disorders in seniors. Currently, there are no mechanisms within primary health care system that would enable proper early screening for dementia in people at the high risk (i.e.> 65 years of age). The development of standards for the early detection of cognitive disorders within primary health care system in Poland seems to be an urgent need.

Classification of mild cognitive impairment based on handwriting dynamics and qEEG

Subtle changes in fine motor control and quantitative electroencephalography (qEEG) in patients with mild cognitive impairment (MCI) are important in screening for early dementia in primary care populations. In this study, an automated, non-invasive and rapid detection protocol for mild cognitive impairment based on handwriting kinetics and quantitative EEG analysis was proposed, and a classification model based on a dual fusion of feature and decision layers was designed for clinical decision-marking. Seventy-nine volunteers (39 healthy elderly controls and 40 patients with mild cognitive impairment) were recruited for this study, and the handwritten data and the EEG signals were performed using a tablet and MUSE under four designed handwriting tasks. Sixty-eight features were extracted from the EEG and handwriting parameters of each test. Features selected from both models were fused using a late feature fusion strategy with a weighted voting strategy for decision making, and classification accuracy was compared using three different classifiers under handwritten features, EEG features and fused features respectively. The results show that the dual fusion model can further improve the classification accuracy, with the highest classification accuracy for the combined features and the best classification result of 96.3% using SVM with RBF kernel as the base classifier. In addition, this not only supports the greater significance of multimodal data for differentiating MCI, but also tests the feasibility of using the portable EEG headband as a measure of EEG in patients with cognitive impairment.

One Minute Early Dementia Screening Test for Indigent Countryside Indian Population: A Community Based Study

AbstractBackgroundWith the ageing of our populations there are increasing numbers of older adults with memory complaints and possible dementia. A new case of dementia in some form is diagnosed every 70 seconds according to the 2010 Alzheimer’s Disease Facts and Figures; moreover countryside population especially indigent population mostly remain undiagnosed. Hence to develop an easy to use dementia detection system has become an international priority for improving care of patients with prevalent neuropsychiatric disorders of later life.Method242 patients were enrolled justifying predesigned inclusion and exclusion criteria after approval from Institutional Ethics Committee. One minute dementia test was administered to them. The 1 minute dementia test is screening tool that had 4 components, testing immediate &amp; delayed recall, orientation, and visuo‐spatial cognition. The Clock Drawing Test (CDT) component of this tool allows clinicians to administer this test among illiterate population and quickly assess numerous cognitive domains. A cutoff score of &lt; 12 was considered abnormal. Receiver operating characteristic, partial correlation and logistic regression analyses were employed for evaluation.ResultIn this study, majority of subjects were greater than 65 years of age. Males accounted for 68% (n = 164) and females for 34% (n = 78). Mean age of the study population was 59.7 ± 13.46 years. A statistically significant decline in cognitive domain were noted in relation to patient education (p&lt;0.001), locality predominantly rural based uneducated population (p&lt;0.001) as well as increasing age (p&lt;0.01) however, no statistically significant correlation (p&gt;0.05) was observed in relation to patient’s sex. Delayed word recall was the most frequently impaired parameter (92.5%; n = 224) followed by visuo‐spatial cognition (82%; n = 198).Immediate recall (4.9%; n = 12) was minimally effected. CDT was abnormal among 69% (n = 168) patientsConclusionIn the present study 87% (n = 210) of the patients had abnormal test. Delayed word recall was the earliest domain to get impaired followed by visuo‐spatial cognition. A cutoff score of &lt; 12 best correlated with risk of detecting dementia. Thus, 1 minute dementia test can be a useful screening tool for detecting dementia in outdoor basis patients though larger studies are required to validate its clinical implications.

Dementia risk predictions from German claims data using methods of machine learning.

We examined whether German claims data are suitable for dementia risk prediction, how machine learning (ML) compares to classical regression, and what the important predictors for dementia risk are. We analyzed data from the largest German health insurance company, including 117,895 dementia-free people age 65+. Follow-up was 10 years. Predictors were: 23 age-related diseases, 212 medical prescriptions, 87 surgery codes, as well as age and sex. Statistical methods included logistic regression (LR), gradient boosting (GBM), and random forests (RFs). Discriminatory power was moderate for LR (C-statistic=0.714; 95% confidence interval [CI]=0.708-0.720) and GBM (C-statistic=0.707; 95% CI =0.700-0.713) and lower for RF (C-statistic=0.636; 95% CI =0.628-0.643). GBM had the best model calibration. We identified antipsychotic medications and cerebrovascular disease but also a less-established specific antibacterial medical prescription as important predictors. Our models from German claims data have acceptable accuracy and may provide cost-effective decision support for early dementia screening.

Early Dementia Questionnaire (EDQ): A Screening Instrument for early Dementia among elderly in Cairo governorate

Abstract Objectives To screen elderly participants for early Dementia in primary care in Egypt using a newly developed Early Dementia Questionnaire (EDQ) and comparing it with standard assessment tool, Mini Mental State Examination (MMSE). Design A cross-sectional study. Setting and Participants The study included 220 elder adults (both men and women) recruited from a primary healthcare center, the outpatient geriatric clinic at Ain Shams University hospitals and elderly clubs (Community dwelling) in Cairo Governorate, Egypt. Methods A cross-sectional study was conducted on a group of elderly patients using systematic random sampling. Elderly depression was excluded using the Geriatric Depression Scale (GDS). Diagnosed cases of dementia and other mental or psychiatric disorders and illiterate participants were excluded from the study. A face-to-face interview was done using EDQ with the participants to elicit symptoms of early dementia. The participants were then assessed with MMSE using variable cut-off points according to age and educational level. Results Prevalence of dementia among the study participants was 81.4% by EDQ and 19.5% by MMSE. The EDQ demonstrated a sensitivity of 97.7% with specificity of 22.6%. Positive predictive value of EDQ was 23.5% with the negative predictive value of 97.6%. A significant association was found between possible dementia, hypertension, Mini Nutritional Assessment and urinary incontinence. Conclusion The EDQ is more sensitive than MMSE for screening of early dementia.

Vestibular Function in Older Adults With Cognitive Impairment: A Systematic Review

Importance: Given the rising prevalence of patients with dementia and those at risk for it, early identification is prioritized. As vestibular dysfunction is associated with Alzheimer’s disease (AD) and may contribute to its onset, vestibular assessment may yield an opportunity in early dementia screening. Objective: This systematic review structures and compares the different raw outcome measures used to assess vestibular function while comparing older adults with preserved cognition to individuals with cognitive impairment, either suffering from mild cognitive impairment (MCI) or AD. Design: Two investigators independently and systematically searched publications performing objectively measured vestibular testing in a patient population consisting of either MCI or AD, compared with a control group of older adults with preserved cognition. No limitations regarding language or publication date were applied. References of the retrieved articles were hand searched for relevant articles. Results: Seven articles were included for analysis. A total of 235 older adults with impaired cognition (150 AD, 85 MCI) were compared with a control group of 481 older adults with preserved cognition. Evaluation of the peripheral vestibular function included video head impulse test (vHIT), videonystagmography (VNG), electronystagmography (ENG) including bithermal caloric irrigation and vestibular evoked myogenic potentials (VEMP). The VEMP test, assessing otolith function and the elicited vestibulocollic reflex (VCR), was able to differentiate subjects with AD and its prodromal stage from healthy controls, with p13 latency (p &lt; 0.05) and amplitude (p &lt; 0.05) having the most discriminating power. No correlation between cognitive decline and vestibulo-ocular reflex measurements in different frequency ranges of the semicircular canals (using vHIT, rotatory chair testing, and caloric irrigation) was found. Because of the limited number of available studies and the large heterogeneity in outcome measures, these results have to be interpreted with caution. Conclusions: Measurements of the VCR, as evoked by the VEMP test, discriminate between patients with cognitive impairment (MCI and AD) and older adults with preserved cognition, whereas measurements of the vestibulo-ocular reflex do not. More studies are needed to further elaborate on these findings.

Predicting the Anxiety of Patients with Alzheimer’s Dementia using Boosting Algorithm and Data-Level Approach

Since overfitting due to imbalanced data can cause prediction errors during the learning process of machine learning and degrades the prediction performance of the model (e.g., sensitivity), it is necessary to add an additional data sampling technique in the model development step to reduce overfitting to overcome this issue, in addition to selecting a machine learning algorithm suitable for the data. This study examined Alzheimer's patients living in South Korea to understand the predictors of anxiety using boosting algorithms (i.e., AdaBoost and XGBoost) and data-level approach (raw data, undersampling, oversampling, and SMOTE) and confirmed the machine learning algorithm with the best prediction performance. We analyzed 253 elderly people who were diagnosed with Alzheimer's disease (aged from 60 to 74 years old) who visited rehabilitation hospitals for early dementia screening. This study developed models for predicting the anxiety of Alzheimer's dementia patients using AdaBoost and XGBoost. Moreover, this study compared the prediction performance (i.e., accuracy, sensitivity, and specificity) of the models. The results of this study showed that XGBoost based on SMOTE (accuracy=0.84, sensitivity=0.85, and specificity=0.81) was identified as the model with the best prediction performance. Consequently, the results of this study presented that using a SMOTE-XGBoost model may provide higher accuracy than using a SMOTE-Adaboost model for developing a prediction model using outcome variable imbalanced data such as disease data in the future.

Triggering Postural Movements With Virtual Reality Technology in Healthy Young and Older Adults: A Cross-Sectional Validation Study for Early Dementia Screening.

With the ultimate aim of early diagnosis of dementia, a new body balance assessment system with integrated head-mounted display-based virtual reality (VR) has been developed. We hypothesized that people would sway more in anterior-posterior (AP) direction when they were exposed to a VR environment where we intentionally provoked movements in forward and backward directions. A total of 14 healthy older adults (OA) (73.14±4.26 years) and 15 healthy young adults (YA) (24.93±1.49 years) were assessed for group differences in sway behavior. Body sway speed in 22 different conditions with and without VR environments was analyzed. Significant differences and large effect sizes were observed in AP sway under the VR environments (OA with P < 0.02; effect size> 0.61, YA with P < 0.003; effect size> 0.72) compared to the baseline condition without the VR environments. In addition, significant differences were found between the two groups in AP sway in all test conditions (P < 0.01). Our study shows that a VR environment can trigger body sway in an expected direction, which may indicate that it is possible to enhance the sensitivity of balance assessment by integrating immersive VR environments. The result of this study warrants a cross-sectional study in which OA diagnosed with and without dementia are compared on their sway behavior.

Practicality of promoting brain health and early dementia screening in elderly residents with friendly mobile App: Beijing plan

This article presents a brief introduction of Beijing plan, namely the Beijing’s Brain Health Examination (dementia risk screening) project initiated by Beijing municipal government in early 2019, which is a successful exploration and practicality of brain health examination for the community residences and dementia risk screening system construction. Slowing down the incidents of dementia and reducing eventually its prevalence in the population has been one of the main targets highlighted in Healthy China Initiative 2030 , by Chinese government. As a welfare to its elderly residents, Beijing municipal government initiated the brain health examination (dementia risk screening) project, aiming to provide brain health examination service for 96000 permanent residences over 65 years old at six districts in Beijing before the end of 2019 and gradually make the service available city-wide. This project is a first yet crucial step that governments, central or local, take the lead and concrete measure to organize and implement brain health examination for the aged on a large scale, and to make the nation’s strategy of healthy China a reality by 2030. Through the early detection and reduction of dementia prevalence, the project would make optimal allocation of medical resources possible and bring enormous social and economic benefit. For example, it will save an estimated cost of 23.36 billion yuan for healthcare in five years only in Beijing area. As an institute involved in the early conceptualization and initiation of this project, the Center for Beijing Aging Brain Rejuvenation Initiative (BABRI) and State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University have been working on AD risk longitudinal research (BABRI project) primarily community-cohort based and later with the added clinical-based cohort since 2008. Based on our ten-year basic research and technology advancement, we built a state-of-art mobile platform with innovative cognitive and mental tests as well as the well-known standard ones. It also includes dementia risk screening system and has been used for the Brain Health Examination (Dementia Risk Screening) project successfully. This platform endows the advantages of high screening efficiency, uses shorter time and is designed for its convenience for the elderly. In addition, it is also a platform for basic scientific research by providing comprehensive data managements, and curative effect assessment of cognitive rehabilitation training. And it’s a technological answer to problems faced by large-scale community-based dementia risk screening. In summary, the Beijing’s Brain Health Examination project not only lays the foundation for carrying out the citywide screening for the aged as a social welfare, but also plays a trend-leading role for the establishment of a government sponsored system for brain health in major provinces and cities of China.

Verbal fluency as a screening tool for mild cognitive impairment.

The goal of this study was to evaluate the ability of semantic (animal naming) and phonemic (FAS) fluency in their ability to discriminate between normal aging, amnestic-Mild Cognitive Impairment (a-MCI), and Alzheimer's disease (AD). We used binary logistic regressions, multinomial regressions, and discriminant analysis to evaluate the predictive value of semantic and phonemic fluency in regards to specific diagnostic classifications. Outpatient geriatric neuropsychology clinic. 232 participants (normal aging = 99, a-MCI = 90, AD = 43; mean age = 65.75 years). Mini-mental State Examination (MMSE), Controlled Oral Word Association Test. Results indicate that semantic and phonemic fluency were significant predictors of diagnostic classification, and semantic fluency explained a greater amount of the discriminant ability of the model. These results suggest that verbal fluency, particularly semantic fluency, may be an accurate and efficient tool in screening for early dementia in time-limited medical settings.

The Digital Tree Drawing Test for Screening of Early Dementia: An Explorative Study Comparing Healthy Controls, Patients with Mild Cognitive Impairment, and Patients with Early Dementia of the Alzheimer Type.

The digital tree drawing test (dTDT) is a newly developed screening tool for the early detection of Alzheimer's disease. It is performed with a digitizing pen, recording each pen stroke with temporal and spatial precision. It was hypothesized that movement characteristics recorded during the painting process contribute to the identification of patients with mild cognitive impairment (MCI) and early dementia of the Alzheimer type (eDAT). The study population consisted of 187 participants (67 healthy controls, 64 MCI, and 56 eDAT patients) with a mean age of 68.6±10.6 years. Between-group comparisons of the dTDT-variables were conducted with analysis of variance. The diagnostic power of dTDT variables was analyzed with stepwise logistic regressions and areas under curve (AUC) of receiver operating control curves. Cognitively impaired persons used less colors and line widths and changed them less often than healthy subjects (p-values ≤0.05). Compared to control, eDAT patients had larger not-painting periods, were slower, and their pictures had less contrast, image size, and complexity (p-values ≤0.01). Logistic regression models of stepwise selected dTDT variables resulted in an AUC of 0.84 (95% confidence interval (CI) [0.79, 0.90], sensitivity = 0.78, specificity = 0.77) for discriminating healthy subjects from all cognitive impaired, an AUC of 0.77. (95% CI [0.69; 0.85], sensitivity = 0.56, specificity = 0.83) for discriminating healthy controls from MCI patients and an AUC of 0.90 (95% CI [0.84, 0.96], sensitivity = 0.86, specificity = 0.82) for discriminating controls from eDAT patients. The results suggest that digital recording of pen-stroke data during the drawing process can contribute to the screening of cognitive impaired patients.

An exploratory study on the prevalence of early dementia among geriatric population in a rural area of district Jammu

Background: Dementia is one of the major causes of disability and dependency among older people worldwide. Dementia can no longer be neglected but should be considered as a public health priority especially by those who are involved in framing and implementing various health policies and programmes. Community based screening to detect dementia in undiagnosed individuals is emerging as a promising health promotion strategy. Methods: The present study was an exploratory cross sectional community based study, conducted in rural area of Jammu region in the month of July and August 2016 among all individual aged 60 years or more who were willing to participate in the study. A brief informant-based screening questionnaire, namely the Symptoms of Early Dementia-11 Questionnaire (SED-11Q) for screening of early dementia was used. Results: A total of 129 individuals participated in the study and out of them 18 persons were categorised to be suffering from early dementia using SED-11Q with overall prevalence rate of 13.95%. Dementia was more common among females as compared to males and prevalence of dementia was highest among people belonging to lowermiddle and middle socioeconomic classes. Conclusions: The SED-11Q categorised nearly 13.95% asymptomatic individuals to be suffering from dementia which is an alarming figure considering it as a disease which affects quality of life and contributes to morbidity of affected individuals.

Reliability and construct validity of the Early Dementia Questionnaire (EDQ).

BackgroundEarly Dementia Questionnaire (EDQ) was developed as a screening tool to detect patients with early dementia in primary care. It was developed based on 20 symptoms of dementia. From a preliminary study, EDQ had been shown to be a promising alternative for screening of early dementia. This study was done to further test on EDQ’s reliability and validity.MethodsUsing a systematic random sampling, 200 elderly patients attending primary health care centers in Kuching, Sarawak had consented to participate in the study and were administered the EDQ. Geriatric Depression Scale (GDS) was used to exclude patients with depression. Those who scored >21 MMSE, were retested using the EDQ. Reliability was determined by Cronbach’s alpha for internal consistency and construct validity was assessed using confirmatory factor analysis (principle component with varimax rotation). Test retest Intraclass Correlation Coeeficient (ICC) was used to determine the reliability of the scale.ResultsThe result showed that the sensitivity and specificity for EDQ was 71.2% and 59.5%. The overall Cronbach’s alpha coefficient was good which was 0.874. Confirmatory factor analysis on 4 factors indicated that the Cronbach’s alpha for each domain were acceptable with memory (0.741), concentration (0.764), emotional and physical symptoms (0.754) and lastly sleep and environment (0.720). The Intraclass Correlation Coefficient between the first EDQ score and the retest EDQ score among those with MMSE of >21 showed a very strong overall agreement, ICC = 0.764, N = 160, P <0.001.ConclusionsThe results of the validation study showed that Early Dementia Questionnaire (EDQ) is a valid and reliable tool to be used as a screening tool to detect early dementia in primary care.

Two-stage screening for early dementia in primary care

ABSTRACTObjective: The objective was to compare two screening strategies for dementia in an urban primary care clinic, serving a low-education, minority community composed largely of Latino and African American patients. Method: Two hundred and fifty-seven patients underwent two-stage patient-based screening (PBS) and informant-based screening (IBS) followed by a diagnostic evaluation. In the first stage, PBS included brief tests of episodic memory (Memory Impairment Screen), semantic memory (Animal Fluency), and executive function (Reciting Months Backwards). For IBS, the first stage consisted of the short Informant Questionnaire on Cognitive Decline in the Elderly, administered to a family member or friend. Patients who screened positive in the first stage of either strategy underwent testing with the picture version of the Free and Cued Selective Reminding Test with Immediate Recall to identify memory impairment. Sensitivity, specificity, and positive and negative predictive values were computed for various cutoffs of each test and combination of tests. Dementia was diagnosed using Diagnostic and Statistical Manual of Mental Disorders–Fourth Edition (DSM–IV) criteria without access to the screening test results. Results: We identified 66 patients (25.7%) with previously undiagnosed dementia. Sensitivity was the same (77%) for both strategies but specificity was higher for IBS than for PBS (92% versus 83%). IBS’s higher specificity makes it the preferred strategy if a knowledgeable informant is available. Conclusion: Unrecognized dementia is common in primary care. Case-finding can be improved using either PBS or IBS two-stage screening strategies.

Early Dementia Screening.

As the population of the world increases, there will be larger numbers of people with dementia and an emerging need for prompt diagnosis and treatment. Early dementia screening is the process by which a patient who might be in the prodromal phases of a dementing illness is determined as having, or not having, the hallmarks of a neurodegenerative condition. The concepts of mild cognitive impairment, or mild neurocognitive disorder, are useful in analyzing the patient in the prodromal phase of a dementing disease; however, the transformation to dementia may be as low as 10% per annum. The search for early dementia requires a comprehensive clinical evaluation, cognitive assessment, determination of functional status, corroborative history and imaging (including MRI, FDG-PET and maybe amyloid PET), cerebrospinal fluid (CSF) examination assaying Aβ1–42, T-τ and P-τ might also be helpful. Primary care physicians are fundamental in the screening process and are vital in initiating specialist investigation and treatment. Early dementia screening is especially important in an age where there is a search for disease modifying therapies, where there is mounting evidence that treatment, if given early, might influence the natural history—hence the need for cost-effective screening measures for early dementia.

Early Dementia Screening: First, Do No Harm

As the population ages, we recognize the serious implications of the increasing number of individuals who will be diagnosed with Alzheimer disease